ArticleBMC systems biology2014
An integrative approach for measuring semantic similarities using gene ontology.
Article in BMC systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- GOntoSim: a semantic similarity measure based on LCA and common descendants.Scientific reports · 2022Article
- Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach.BMC systems biology · 2018Article
- Investigations on factors influencing HPO-based semantic similarity calculation.Journal of biomedical semantics · 2017Article
- Predicting disease-related genes using integrated biomedical networks.BMC genomics · 2017Article
- Constructing Networks of Organelle Functional Modules in Arabidopsis.Current genomics · 2016Article
- InteGO2: a web tool for measuring and visualizing gene semantic similarities using Gene Ontology.BMC genomics · 2016Article
- The Genome Conformation As an Integrator of Multi-Omic Data: The Example of Damage Spreading in Cancer.Frontiers in genetics · 2016Article
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Authors and funding
5 authors.
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Abstract
backgroundGene Ontology (GO) provides rich information and a convenient way to study gene functional similarity, which has been successfully used in various applications. However, the existing GO based similarity measurements have limited functions for only a subset of GO information is considered in each measure. An appropriate integration of the existing measures to take into account more information in GO is demanding.
resultsWe propose a novel integrative measure called InteGO2 to automatically select appropriate seed measures and then to integrate them using a metaheuristic search method. The experiment results show that InteGO2 significantly improves the performance of gene similarity in human, Arabidopsis and yeast on both molecular function and biological process GO categories.
conclusionsInteGO2 computes gene-to-gene similarities more accurately than tested existing measures and has high robustness. The supplementary document and software are available at http://mlg.hit.edu.cn:8082/.
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